# ai-memory — AI Coding Tool Review & Pricing

> ai-memory is a long-term memory server for coding agents that captures session lifecycles into a git-versioned markdown wiki. It enables seamless handoffs across different coding agents, machines, and team members by maintaining a shared, queryable knowledge base.

Source: https://ai.dosa.dev/tools/ai-memory · Updated Nov 1, 2026 · Category: Developer Productivity & Workflow · Published by dosa.dev

## At a glance

- **Tool**: ai-memory
- **Company**: AkitaOnRails
- **Category**: [Developer Productivity & Workflow](https://ai.dosa.dev/category/productivity)
- **Pricing model**: Open Source
- **Official website**: https://github.com/akitaonrails/ai-memory

## Key features

- Cross-agent memory sharing for 20+ harnesses including Claude Code and Cursor
- Zero-LLM operation by default with local FTS5, entity, and graph retrieval
- Git-backed markdown wiki as the primary source of truth
- Multi-user synchronization with per-person attribution and audit logs
- Self-contained single binary architecture with no external dependencies

## Pricing

**Model**: Open Source

Distributed as a free, open-source MIT-licensed tool with no paid tiers; all features including multi-user auth, audit logs, and attribution are included in the single binary.

## Who it is for

- **Best for**: Developers or teams using multiple AI coding agents who need consistent context and project history persistence across different tools, machines, and sessions.
- **Not ideal for**: Users seeking a managed, cloud-hosted SaaS platform, as this tool is designed for self-hosting on personal machines, homelabs, or local network servers.

## Verdict

An exceptional, privacy-focused solution for power users who want a durable, vendor-neutral memory layer that stays under their control without relying on proprietary cloud silos.

## Recent updates

Version 3.3.1 (2026-11-01) improved hook handling, Claude Code tool failure capture, and integration reliability. Version 3.3.0 (2026-10-30) introduced a new agent dashboard, message inbox for authorized users, and atomic section editing.

## Frequently asked questions

### Is ai-memory free?

Yes - ai-memory is Open Source. Distributed as a free, open-source MIT-licensed tool with no paid tiers; all features including multi-user auth, audit logs, and attribution are included in the single binary.

### Is ai-memory open source?

Yes - ai-memory is open source. Distributed as a free, open-source MIT-licensed tool with no paid tiers; all features including multi-user auth, audit logs, and attribution are included in the single binary.

### Who is ai-memory best for?

Developers or teams using multiple AI coding agents who need consistent context and project history persistence across different tools, machines, and sessions.

### Who is ai-memory not ideal for?

Users seeking a managed, cloud-hosted SaaS platform, as this tool is designed for self-hosting on personal machines, homelabs, or local network servers.

### What are the best ai-memory alternatives?

The closest ai-memory alternatives on ai.dosa.dev are Pieces for Developers, agenttrace, Vibe Kanban - all listed under Developer Productivity & Workflow.

### Who makes ai-memory?

ai-memory is developed by AkitaOnRails. It is listed in the Developer Productivity & Workflow category on ai.dosa.dev.

## Top alternatives

- [Pieces for Developers](https://ai.dosa.dev/tools/pieces-for-developers) (Paid) — Developers who work across multiple tools, IDEs, and environments and need to maintain a persistent, searchable history of code snippets, research, and workflow context.
- [agenttrace](https://ai.dosa.dev/tools/agenttrace) (Open Source) — Developers and teams needing to monitor and debug the efficiency, cost, and health of AI coding agents across multiple workflows.
- [Vibe Kanban](https://ai.dosa.dev/tools/vibe-kanban) (Open Source) — Software engineers who use multiple AI coding agents and need a structured environment to manage, plan, and review their output in parallel.
- [smolvm](https://ai.dosa.dev/tools/smolvm) (Open Source) — Running isolated coding agent sandboxes, untrusted code, and persistent local development environments that require a real Linux kernel boundary.
- [coop](https://ai.dosa.dev/tools/coop) (Open Source) — Running autonomous AI coding agents that require broad system access while maintaining a strong security boundary for the host machine.
- [SPACE](https://ai.dosa.dev/tools/space) (Open Source) — Teams needing to self-host a robust, secure, and isolated sandbox environment for long-running autonomous AI agents on their own infrastructure.
- Full alternatives guide: https://ai.dosa.dev/tools/ai-memory/alternatives